Ë
    ÛÓ^j0  ã                   ój   — d Z ddlmZ ddlmZ ddlmZ  ed¬«      e G d„ d	e«      «       «       Zd	gZy
)zDeBERTa model configurationé    )Ústricté   )ÚPreTrainedConfig)Úauto_docstringzmicrosoft/deberta-base)Ú
checkpointc                   ó¬  ‡ — e Zd ZU dZdZdZeed<   dZeed<   dZ	eed<   dZ
eed	<   d
Zeed<   dZeed<   dZeez  ed<   dZeez  ed<   dZeed<   dZeed<   dZeed<   dZeed<   dZeed<   dZeed<   dZedz  ed<   dZedz  ed<   dZeee   z  dz  ed <   d!Zeed"<   dZeee   z  dz  ed#<   d$Zeez  ed%<   dZeed&<   d!Z eed'<   d!Z!eed(<   ˆ fd)„Z"ˆ xZ#S )*ÚDebertaConfigaí  
    relative_attention (`bool`, *optional*, defaults to `False`):
        Whether use relative position encoding.
    max_relative_positions (`int`, *optional*, defaults to -1):
        The range of relative positions `[-max_position_embeddings, max_position_embeddings]`. Use the same value
        as `max_position_embeddings`.
    position_biased_input (`bool`, *optional*, defaults to `True`):
        Whether add absolute position embedding to content embedding.
    pos_att_type (`list[str]`, *optional*):
        The type of relative position attention, it can be a combination of `["p2c", "c2p"]`, e.g. `["p2c"]`,
        `["p2c", "c2p"]`.
    pooler_dropout (`float`, *optional*, defaults to `0`):
        Dropout rate in the pooler module.
    pooler_hidden_act (`str`, *optional*, defaults to `"gelu"`):
        Activation function used in the dropout module.
    legacy (`bool`, *optional*, defaults to `True`):
        Whether or not the model should use the legacy `LegacyDebertaOnlyMLMHead`, which does not work properly
        for mask infilling tasks.

    Example:

    ```python
    >>> from transformers import DebertaConfig, DebertaModel

    >>> # Initializing a DeBERTa microsoft/deberta-base style configuration
    >>> configuration = DebertaConfig()

    >>> # Initializing a model (with random weights) from the microsoft/deberta-base style configuration
    >>> model = DebertaModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```ÚdebertaiYÄ  Ú
vocab_sizei   Úhidden_sizeé   Únum_hidden_layersÚnum_attention_headsi   Úintermediate_sizeÚgeluÚ
hidden_actgš™™™™™¹?Úhidden_dropout_probÚattention_probs_dropout_probi   Úmax_position_embeddingsr   Útype_vocab_sizeg{®Gáz”?Úinitializer_rangegH¯¼šò×z>Úlayer_norm_epsFÚrelative_attentionéÿÿÿÿÚmax_relative_positionsNÚpad_token_idÚbos_token_idÚeos_token_idTÚposition_biased_inputÚpos_att_typeg        Úpooler_dropoutÚpooler_hidden_actÚlegacyÚtie_word_embeddingsc                 ó8  •— t        | j                  t        «      rJ| j                  j                  «       j	                  d«      D �cg c]  }|j                  «       ‘Œ c}| _        |j                  d| j                  «      | _        t        ‰| �(  di |¤Ž y c c}w )Nú|Úpooler_hidden_size© )Ú
isinstancer    ÚstrÚlowerÚsplitÚstripÚgetr   r'   ÚsuperÚ__post_init__)ÚselfÚkwargsÚxÚ	__class__s      €ú|/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/site-packages/transformers/models/deberta/configuration_deberta.pyr0   zDebertaConfig.__post_init__U   sw   ø€ ä�d×'Ñ'¬Ô-Ø48×4EÑ4E×4KÑ4KÓ4M×4SÑ4SÐTWÓ4XÖ Y¨q §¡¥Ò YˆDÔà"(§*¡*Ð-AÀ4×CSÑCSÓ"TˆÔÜ‰ÑÑ' Ó'ùò !Zs   ÁB)$Ú__name__Ú
__module__Ú__qualname__Ú__doc__Ú
model_typer   ÚintÚ__annotations__r   r   r   r   r   r*   r   Úfloatr   r   r   r   r   r   Úboolr   r   r   r   Úlistr   r    r!   r"   r#   r$   r0   Ú__classcell__)r4   s   @r5   r	   r	      s:  ø… ñ ðD €Jà€J�ÓØ€K�ÓØÐ�sÓØ!Ð˜Ó!Ø!Ð�sÓ!Ø€J�ÓØ'*Ð˜ ™Ó*Ø03Ð  %¨#¡+Ó3Ø#&Ð˜SÓ&Ø€O�SÓØ#Ð�uÓ#Ø €N�EÓ Ø$Ð˜Ó$Ø"$Ð˜CÓ$Ø €L�#˜‘*Ó Ø#€L�#˜‘*Ó#Ø+/€L�#˜˜S™	‘/ DÑ(Ó/Ø"&Ð˜4Ó&Ø+/€L�#˜˜S™	‘/ DÑ(Ó/Ø"%€N�E˜C‘KÓ%Ø#Ð�sÓ#Ø€FˆDÓØ $Ð˜Ó$÷(ð (ó    r	   N)	r9   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r	   Ú__all__r(   rA   r5   ú<module>rF      sK   ðñ "å .å 3Ý #ñ Ð3Ô4ØôC(Ð$ó C(ó ó 5ðC(ðL Ð
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